The Natural Language Processing (NLP) track is intended for students who wish to gain expertise in NLP technologies and applications. NLP technologies are of central importance in automating the analysis of text and speech databases and in enabling man-machine interactions through natural language. This track will help you develop leading edge knowledge of these technologies.
1. Overall Requirements
Students must complete at least a total of 30 graduate credits.
Fulfill the 12-credit core requirement
COMS W4701 is a prerequisite for this track
3 courses (9 credits) are required by the track: COMS W4705 (NLP), COMS W4706 (Spoken Language Processing), and COMS E6998 (Advanced NLP Topics)
2 elective courses (6 credits) selected from the list of section 4; at least one of these courses must be a 6000-level CS course
1 general elective graduate CS course (3 credits) at 4000 level or above
2. Core Requirements
For the 12-credit core requirement, students take 4 courses from the following 6. Candidates must complete the core course COMS-W4701 to develop a fundamental understanding of AI.
COMS W4115 Programming Languages & Translators
COMS W4118 Operating Systems
COMS W4156 Advanced Software Engineering
CSOR W4231 Analysis of Algorithms
COMS W4701 Artificial Intelligence
CSEE W4824 Computer Architecture
3. Required Track Courses
Candidates are required to complete the following three courses:
Natural Language Processing
Spoken Language Processing
Topic courses that focus on NLP
Students who have completed equivalent courses with grades of at least 3.0 may apply these courses to satisfy these requirements and devote more credits to pursue elective courses.
4. Elective Track Courses
are required to complete two (2) courses out of the following list*; at
least one course must be a 6000-level CS course.
Since other departments vary their offerings considerably from year to year, it is possible to count such courses toward the M.S. degree; please propose courses you think might be suitable to the track advisor.
User Interface Design
3D User Interfaces
Introduction to Computational Learning Theory
Projects in Computer Science
Search Engine Technology
|NLP for the Web |
|COMS E6998 ||Statistical Methods for NLP |
|COMS E6998 ||Machine Learning for NLP |
|COMS E6998 ||Adv. Topics in Machine Learning |
|Fundamentals/Speaker Recognition |
Probability and Statistics
Digital Signal Processing
Production and Perception of Language
Contemporary Topics in Language and Communication
Models of Cognition
Psychology and Neuropsychology of Language
Introduction to Statistical Modeling in Psychology
5. General Electives
Candidates are required to complete at least one Columbia graduate course, approved by the Track Advisor. Please complete a non-tech approval form, and once it is signed, forward it to Janine Maslov or Remi Moss. At most 3 credits overall of the 30 graduate credits required for the MS degree may be non-technical.
6. Track Planning
CS course-offering schedule (Please note that the course-offering schedule can change due to unforeseeable circumstances; thus, it should only be used as a reference).
Please direct all questions concerning the NLP Track to Prof. .
Candidates preparing for graduation should submit a completed application for degree to the Registrar's Office and submit a track graduation form to C.S. Student Services (an example of a completed form is available here).
*The list of electives may be updated to reflect changes in the schedule of course offerings.
**Please note that these course offerings are listed on a provisional basis only and may change from what is listed here.
Last updated 5/23/2012